Evidence map›Paper›PMID 29466849›Full record

ArticleThe Korean journal of internal medicine2018

Predictors of postoperative infectious complications in liver transplant recipients: experience of 185 consecutive cases.

Seungjin Lim, Eun Jung Kim, Tae Beom Lee, Byung Hyun Choi, Young Mok Park, Kwangho Yang, Je Ho Ryu, Chong Woo Chu, Su Jin Lee

Abstract read
In one paragraph

Article in The Korean journal of internal medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Meta-analysis and meta-regression of outcomes for adult living donor liver transplantation versus deceased donor liver transplantation.American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2021
    Pooled it
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Predicting VRE Infection After Liver Transplantation With a Time-Updated Colonization Score.Transplant infectious disease : an official journal of the Transplantation Society
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Seungjin LimDepartment of Internal Medicine, Pusan National University School of Medicine, Yangsan, Korea.
Eun Jung KimDepartment of Internal Medicine, Pusan National University School of Medicine, Yangsan, Korea.
Tae Beom LeeDepartment of Surgery, Pusan National University Yangsan Hospital, Yangsan, Korea.
Byung Hyun ChoiDepartment of Surgery, Pusan National University Yangsan Hospital, Yangsan, Korea.
Young Mok ParkDepartment of Surgery, Pusan National University Yangsan Hospital, Yangsan, Korea.
Kwangho YangDepartment of Surgery, Pusan National University Yangsan Hospital, Yangsan, Korea.
Je Ho RyuDepartment of Surgery, Pusan National University Yangsan Hospital, Yangsan, Korea.
Chong Woo ChuDepartment of Surgery, Pusan National University Yangsan Hospital, Yangsan, Korea.
Su Jin LeeDepartment of Internal Medicine, Pusan National University School of Medicine, Yangsan, Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background/Aims: Infections following liver transplant (LT) remain a major cause of mortality. This study was conducted to evaluate risk factors for infection and to review clinical characteristics.

methodsMedical records of patients who underwent LT from 2010 to 2014 were retrospectively analyzed. Binary logistic regression analysis was used to investigate risk factors of infection. Kaplan-Meier analysis was used to predict prognosis of infected and non-infected groups.

resultsOf 185 recipients, 89 patients experienced infectious complications. The median follow-up period was 911 days (range, 9 to 2,031). The infected group had higher 1-year mortality (n = 22 [24.7%] vs. n = 8, [8.3%], p = 0.002), and longer postoperative admission days (mean: 53.7 ± 35.8 days vs. 28.3 ± 13.0 days, p < 0.001), compared to the non-infected group. High preoperative Model for End-Stage Liver Disease (MELD) score (odds ratio [OR], 1.057; 95% confidence interval [CI], 1.010 to 1.105; p = 0.016), deceased-donor type (OR, 5.475; 95% CI, 2.442 to 12.279; p < 0.001), and acute rejection (OR, 3.042; 95% CI, 1.241 to 7.454; p = 0.015) were independent risk factors associated with infection. Intra-abdominal infection (n = 35, 20.8%) was the major infectious complication. Among identified bacteria, Enterococcus species (28.4%) were major pathogens, followed by Escherichia coli and Klebsiella species. Conclusions: High preoperative MELD score, deceased-donor type, and acute rejection were risk factors associated with infection. To prevent infections following surgery, it is important to determine the appropriate time of operation before the recipient has a high MELD score.

Indexed as

InfectionsLiver TransplantationPostoperative ComplicationsAdolescentAdultAgedChildFemaleHumansMaleMiddle AgedRepublic of KoreaRetrospective StudiesRisk FactorsTreatment OutcomeYoung AdultInfectionLiver transplantationRisk factors

Identifiers

PMID29466849
PMCPMC6030419

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.